Slow pion identification at the Belle II PXD with machine learning

Sumitted to PubDB: 2024-02-26

Category: Talk, Visibility: Public

Tags: -

Authors	Johannes Bilk, Stephanie Kaes, Elisabetta Prencipe, Timo Schellhaas
Non-Belle II authors	Sören Lange
Date	Feb. 26, 2024
Belle II Number	BELLE2-TALK-CONF-2024-017
Abstract	The identification of slow pions in Belle II experiments presents a no- table challenge, arising from their high dE/dx energy loss and their short flight path in the tracking detectors. This study introduces a method employing advanced machine learning algorithms to accurately detect pions with momentum p<100 MeV/c exclusively with the Belle II pixeldetector (PXD). By analyzing detector signals (in particular a 9x9 pixel matrix) with image processing and pattern recognition methods, this approach significantly boosts the efficiency and accu- racy. Offline and online (FPGA) implemenation will be discussed.
Conference	DPG-Frühjahrstagung Karlsruhe